2016 INFORMS Annual Meeting Program

SD53

INFORMS Nashville – 2016

SD51

2 - Identifying Optimal Multi-state Collaborations For Reducing Co2 Emissions By Co-firing Biomass In Coal-burning Power Plants Bayram Dundar, University of Missouri, Columbia, MO, 65201- 3738, United States, Bd5zc@mail.missouri.edu Ronald McGarvey, Francisco X Aguilar EPA has recently proposed a rule that aims to achieve a total US carbon emission reduction of 32 percent below 2005 levels by 2030. An increase in co-firing woody biomass with coal is one approach electricity providers could take towards achieving these reductions. We develop a mixed integer linear programming model to identify min-cost approaches for reducing carbon emissions via biomass co-firing subject to spatially-explicit biomass availability constraints, utilizing a robust optimization approach to address uncertainties in power plant modification costs and emission rates. We apply this model to a set of 18 states in the northern US to identify optimal sets of multi-state collaborations. 3 - Estimates Of Successful Illegal Entry Across The U.S. Southwest Land Border Brian Rieksts, Institute for Defense Analyses, brieksts@ida.org We present a methodology to estimate successful illegal entry across the United States southwest land border. A repeated trials model based on repeated apprehensions was used to estimate these flows. Both administrative data and survey data were evaluated and used to construct these estimates. 4 - A Robust Optimization Evaluation Of The Potential For Reliance On Locally-produced Foods Ronald G. McGarvey, University of Missouri, Columbia, MO, United States, mcgarveyr@missouri.edu, Bayram Dundar, Christine Costello Strategies focused on local food production may generate new risks due to yield variability. We develop a robust optimization (RO) model to determine, for a given center C, the minimum radius R of a circle containing sufficient cropland and pasture to produce food items that satisfy the calorie and nutrient needs of the population residing within distance R of any point within that circle. We first run the model using historical yield averages for two US cities, assuming no variability. We then run our RO model using historical yield data over ten years to estimate variability. We compare the two model results to illustrate the impact of data uncertainty on meeting sustainable local food for communities. SD53 Music Row 1- Omni Organizational Innovation Sponsored: Technology, Innovation Management & Entrepreneurship Sponsored Session Chair: Sinan Erzurumlu, Babson College, 231 Forest St, Brookline, MA, 02457, United States, serzurumlu@babson.edu 1 - Business Start-up Operations Nitin Joglekar, Boston University School of Management, joglekar@bu.edu Evidence on operational innovations (OI), based on connectivity based analytics and low cost intelligent robotics, points to the co-evolution between business models and OI. We argue that this evolution offers opportunities to develop new types of decision support models. 2 - Communication, Incentives, And The Execution Of A Strategic Initiative Jeremy Hutchison-Krupat, University of Virginia, krupatj@darden.virginia.edu Senior leadership can influence a direct report through incentives and communication. Financial incentives are credible and precisely specified, but offer limited flexibility, whereas communication is flexible, but lacks precision and must be deemed credible to affect a direct report’s actions. We study senior leadership who seeks to add an initiative to their portfolio. Early on, its potential to create value is not well-understood, however, senior leadership eventually obtains knowledge on its potential which they may communicate to their direct report. 3 - Relationship-specific Agreements Between The Service Provider And The Firm In The Gig Economy Sinan Erzurumlu, Babson College, serzurumlu@babson.edu Jonathan Sims In this research we explore the interactions between the service providers and the firm in the gig economy. We analyze survey data to understand the relationship- specific norms and agreements between the service provider and the firm through the lens of psychological contracting.

213-MCC Decision-making Models for Public Health Systems Sponsored: Public Sector OR Sponsored Session Chair: Chaitra Gopalappa, University of Massachusetts - Amherst, 120D Marston Hall, 160 Governors Drive, Amherst, MA, 01003, United States, chaitrag@umass.edu 1 - Estimating Disease Burden Of A Potential H7N9 Pandemic Influenza Outbreak In The United States Walter Silva Sotillo, USF, silvasotillo@mail.usf.edu Recent emergence of H7N9 influenza virus in China resulted in 571 laboratory- confirmed cases of human infections causing 212 deaths (37% fatality rate). Researchers have developed early estimates of some of the epidemiological parameters to characterize H7N9 virus in China. We use data from recent reports, an agent-based simulation model and stratified sampling to estimate disease burden of a potential H7N9 pandemic outbreak in the United States. 2 - Using The HIV Optimization And Prevention Economics (HOPE) Model For Evaluating HIV Interventions In The United States Emine Yaylali, Centers for Disease Control and Prevention, The HOPE model is a detailed, dynamic compartmental model of HIV disease progression and transmission in the United States. We parametrized and calibrated the model to closely match the population of people living with HIV between 2006 and 2010, to project HIV transmission into the future. The population was stratified by age, sex, circumcision status, race/ethnicity, transmission group, and risk level. Outcomes included HIV incidence, prevalence, and care status. We employed the HOPE model to evaluate the cost-effectiveness of HIV interventions and explore HIV prevention policy questions. 3 - Access-to-Medicines (ATM) Vaccine Supply Chain Design: Astakeholder Framework Nico Vandaele, KU Leuven, Naamsestraat 69, Leuven, 3000, Belgium, nico.vandaele@kuleuven.be Catherine Jenny Decouttere, Mauro Bernuzzi, Stef Lemmens Supply chains supportive of ATM, like vaccine supply chains, impose considerable additional challenges on the supply chain design process. We embed the modeling in a broader stakeholder based framework, which will substantially enhance the societal and human impact of the ATM supply chain service delivery. Our approach contains stakeholder mapping and system delineation, key performance indicator development, scenario generation including modelling, scenario ranking and final design selection. 4 - A Methodology For Parameterization Of State-transitions For Cancer Progression In Populations With Limited Longitudinal Cancer Database Chaitra Gopalappa, University of Massachusetts, Amherst, chaitrag@umass.edu, Carel Pretorius, Jeremy Lauer Economic analyses of cancer screening strategies specific to populations in low and middle income countries (LMICs) are limited. Barriers include absence of cancer progression models parameterized specific to these populations. This study addresses this gap. wqq3@cdc.gov, Paul Farnham, Stephanie Sansom, Katherine A. Hicks, Amanda Honeycutt, Emily Tucker

SD52

214-MCC Public Sector OR Problems with Geographic Considerations Sponsored: Public Sector OR Sponsored Session

Chair: Ronald G McGarvey, University of Missouri, E3437D Lafferre Hall, Columbia, MO, 65211, United States, mcgarveyr@missouri.edu 1 - Dynamic Decision Modeling For Inland Waterway Disruptions Rachel Holmer, University of Arkansas, reholmer@email.uark.edu, Hueon Lee, Mahboubeh Madadi, Shengfan Zhang, Heather Nachtmann There is much uncertainty associated with inland waterway transportation. Natural or man-made disruption on the inland waterway system can have widespread economic and societal impacts, and their consequences can be significant. In this research, a Markov decision process model was developed to identify optimal decisions in the event of a weather-related disruption to minimize the barge owner’s loss, incorporating the uncertainty associated with the reopening of the waterway and deteriorating value of the cargo. Historical lock and dam unavailability data and related weather data were collected and analyzed to build a prediction model on lock and dam closure and reopening.

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